A vehicle purchaser can realize fuel savings by purchasing an electrified or semi-electrified vehicle. However, these vehicles are typically more capital intensive to purchase than their conventional vehicle counterparts. Identifying the fuel savings by purchasing an electrified or semi-electrified vehicle can be difficult. Thus, it is important to be able to accurately determine the return-on-investment to the purchaser before purchase. Unfortunately, determination of these savings is difficult due to the high dependency of energy consumption on the real-world drive cycle. Therefore, identifying the appropriate application of hybrid/electric vehicles is important both to the manufacturer of the vehicles, as well as the potential purchaser.
Currently, the vehicle manufacturer either markets the fuel consumption of the vehicle as tested on government mandated test procedures, or as measured in real-world fuel consumption in specific applications. Unfortunately, in most cases purchasers find the true fuel consumption to be greater than that advertised by the manufacturer. This is typically due to a mismatch between the drive cycles that the vehicle is tested on, and the drive cycle that the vehicle is experiencing in use. The net effect is disappointed vehicle purchasers, and negative publicity for these vehicles for not living up to advertised expectations.
Vehicle simulation software is currently available. Two providers of such simulation tools are ANL (PSAT simulation software) and AVL (Advisor simulation software). Typically these tools are used for vehicle design purposes by large automotive design firms. These software packages are extremely complex and their use requires an engineer experienced in vehicle design. They are, for this reason, limited to vehicle manufacturers.
Simple vehicle return on investment (ROI) calculators also exist. These rely on advertised fuel consumption values to determine fuel costs. While this is the obvious approach, experience with hybrid and electric vehicles indicates that these analyses can be very misleading since the advertised fuel consumption can be in significant error due to actual drive cycle.
Calculating the fuel consumption of a vehicle from ODBII diagnostic data is straightforward as provided in Canadian patent application 2,541,593. This method is useful to determine fuel consumption of vehicles already in one's possession, however, it does not solve the issue of predicting fuel consumption of a vehicle (or set of vehicles) before their purchase.
Furthermore, there are methods for estimating the mass of a vehicle, as is provided in U.S. Pat. No. 6,347,269.
Nevertheless, there is no currently existing technique for accurately simulating the fuel usage of a vehicle under consideration for purchase.
What is required, therefore, is a tool for accurately simulating the fuel usage of a vehicle under consideration for purchase.